Abstract:
In a blockchain IoT network, there exists a diversity of devices, including full nodes and light nodes, each with varying capacities and roles. Full nodes have the capability to store the entire ledger, whereas light nodes, constrained by limited memory capacity, cannot store. However, light nodes can efficiently retrieve data from full nodes and actively participate in network transaction approvals, especially in critical applications such as military and healthcare sectors. To enable light nodes to approve transaction by verifying blockchain ledgers we need to determine the nearest distance from a light node to a full node is imperative. While several algorithms exist for this purpose, Routing Protocol for Low-Power and Lossy Networks (RPL) emerges as the optimal choice. In comparison to other algorithms like Dijkstra’s Algorithm, Floyd-Warshall Algorithm, Genetic Algorithms (GA), and Ant Colony Optimization (ACO), RPL stands out with distinct advantages. While Dijkstra’s Algorithm and Floyd-Warshall Algorithm excel in finding shortest paths, they may not be optimized for the unique constraints and dynamics of IoT networks. Genetic Algorithms (GA) offer heuristic solutions but may lack adaptability to real-time changes in network topology, while Ant Colony Optimization (ACO) may face scalability and resource constraints in IoT environments. Conversely, RPL is meticulously tailored for low-power and lossy networks inherent to IoT settings. Its capability to form Directed Acyclic Graphs (DAGs) and dynamically adjust routes based on metrics like hop count and energy efficiency positions it as an ideal choice for determining the nearest distance between light nodes and full nodes in a blockchain IoT network. By capitalizing on its adaptability and efficiency, RPL surpasses other algorithms in enabling efficient data retrieval and facilitating network transaction approvals, thereby ensuring the seamless operation of blockchain IoT systems.
